1. Technical Field
Present invention embodiments relate to performing analytics on data stored within data systems, and more specifically, to validating and visualizing performance of the analytics to ensure proper operation.
2. Discussion of the Related Art
Healthcare networks have very complicated organization structures. An organization typically comprises multiple source systems (e.g., a source of electronic medical records including electronic health records (EHR), records from a claims system, lab feed, various data sources implementing the HL7 standard, patient satisfaction survey, etc.). Clinically integrated networks (CIN) or galaxies (e.g., a group of organizations) are collections of individual healthcare systems with data sharing agreements. Analytics may be applied to the various electronic medical records to produce results for a desired population (e.g., of patients, health care providers, provider organizations or networks, etc.) based upon queries by end users.
The analytics determine measures for particular patient populations, where the measures are defined by specifications within a schema used to analyze the data (e.g., an XML type language). Patients are assigned to categories based on satisfaction of criteria for a measure, and values of organization performance for a measure are determined based on the number of patients in each category. These performance values are utilized to understand the performance of the organization which affects reimbursement or overall cost savings.
When new measures are to be employed, the new measures are validated, typically as user acceptance testing, to ensure that the new measures are working properly and capturing any requested customization. However, this validation process is performed manually, where users receive and manually analyze combinations of specification documents to understand how those measures work and the corresponding criteria. Subsequently, users manually view patient information to identify evidence (or lack of evidence) to apply to measure criteria in order to ensure that the measure is properly sorting patients.
The manual validation process is inefficient due to a lack of understanding by users of the measure criteria which facilitates loss of measure specifics (such as date ranges that apply to certain diagnoses and procedures) and lack of confidence in results. In addition, the process is extremely time intensive since users need to manually search through patient information.